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Data Science vs Statistics
Data Science is an interdisciplinary field that makes use of various tools, techniques & technologies for effective Big Data management & analysis. The data modeling techniques in Data Science enables businesses to process their large reserves of structured and unstructured formats of big data to detect patterns. The insights that are thus generated from Big Data with the application of Data Science would help the enterprises to increase efficiencies, manage costs, explore new revenue opportunities, understand their customers, predict the market trends and stay relevant with the customer & market demand.
Bing an interdisciplinary field, Data Science is the perfect blend of business management, computer science, mathematics, programming, and software engineering along with statistics. Data Scientists will be relying on various tools & statistical modeling techniques to help them in achieve their desired goals. If you are interested in building your career in Data Science then knowledge of statistics becomes very crucial. Develop skills in statistics and several other advanced techniques in Data Science with our Data Science Training In Hyderabad program.
Data Science And Statistics:
Statistics will be playing a crucial role in the field of Data Science & Big Data. There As most of the data that is generated all over the world remains in an unstructured format which also include some non-numeric data. So, to gain insights from these formats of data noise should be eliminated first & then insights are extracted and analyzed.
One of the major essential aspects in relation to performing statistical analysis in Data Science is that statistical tasks would require a specific design and implementation in four data areas namely Data Science Acquisition, Data Architecture, Data Analysis, and Data Archiving.
Use Of Statistics In Data Science:
Statistical modeling technologies & methods will be empowering the Data Scientists to explore deep inside big data & explore insights from more powerful ways and methods. Statistics will also be playing a key role in analyzing and interpreting the results and helps in making accurate conclusions to resolve the concerned problems. Statistical Analysis will also help the Data Scientists in making sure that the obtained results are valid and consistent.
Statistics will also be playing a crucial role in making accurate predictions and insightful inferences from Big Data.
Prominent Statistical Techniques In Data Science
- Generalized linear models
- Time series methods
- Structural equation modeling
- Factor analysis
- K-means clustering
- Bayesian methods
- Statistical inference and group testing
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